水力发电学报2025，Vol.44Issue(8)：57-70,14.DOI:10.11660/slfdxb.20250806
平朔矿区矿井涌水智能溯源及采煤策略干预分析
Intelligent traceability of mine water inrush and intervention analysis of mining strategy in Pingshuo mining area
摘要
Abstract
Mining activities significantly affect ion concentration in groundwater,and changes in mining strategies exhibit notable heterogeneity in their impact on different aquifer lithologies.Traditional methods lack reliability in identifying water sources,since they are based on empirical groundwater chemical characteristics.This study adopts causal inference models to describe the evolution and heterogeneity of water chemical characteristics,and presents a groundwater traceability inference model based on Random Forest(RF)and Generalized Random Forest(GRF).Using nearly 20 years of groundwater chemical data from the Pingshuo mining area,and combining the RF model with data augmentation techniques,we have achieved intelligent traceability of aquifer lithologies with an accuracy of exceeding 97%.The results indicate adjustments in mining strategies have a significant impact on aquifer lithologies,particularly on the water quality from mining voids and sandstone,which exhibits strong heterogeneity in ion concentrations.The heterogeneity further affects the traceability model's classification ability.This study reveals the mechanisms of how certain mining strategy intervention influences the variations in water chemical characteristics in different aquifer lithologies,and helps optimize groundwater resource management in mining areas.关键词
机器学习/智能溯源/地球化学/广义随机森林/异质性分析Key words
machine learning/intelligent traceability/geochemistry/generalized random forest(GRF)/heterogeneity analysis分类
建筑与水利引用本文复制引用
李卫红,王明阳,王聪聪,王恩志,周婷,刘占奎,谷洪彪,贾自立,胡国新..平朔矿区矿井涌水智能溯源及采煤策略干预分析[J].水力发电学报,2025,44(8):57-70,14.基金项目
国家自然科学基金项目(42402263) （42402263）
平朔公司技术服务项目(20232001766) （20232001766）
